Function of finviz.com

二、功能实现

功能一：板块层级图

#使用portfolio包中的map.market函数绘制板块层级图
#绘制沪深300的板块层级图
map.market(id    = HS300$order,
           area  = HS300$mar_cap,
           group = HS300$sector,
           color = HS300$pri_lim,
           lab   = c("group"=TRUE, "id"=FALSE),
           main  = "Map of the Market")

#分组变量是沪深300股票所处行业，面积代表股票市值，颜色代表股票涨跌幅

#绘制沪深300中非银金融行业的板块层级图
finids<-HS300[HS300$sector=='非银金融',]
finids$order<-as.character(finids$order)
finids$mar_cap<-as.numeric(finids$mar_cap)
map.market(id    = finids$order,
           area  = finids$mar_cap,
           color = finids$pri_lim,
           group = finids$name,
           lab   = c("group"=TRUE, "id"=FALSE),
           main  = "Map of the Industry")

#分组变量是非银金融行业股票名称，面积代表股票市值，颜色代表股票涨跌幅

功能二：气泡图

p<-plot_ly(HS300,
           x=~sector,
           y=~pri_lim,
           text=~name,
           type = 'scatter',
           marker = list(size = ~mar_cap/10),
           mode = 'markers',
           color = ~sector
)  %>%
layout(title = 'style bubble',
       xaxis = list(showgrid = FALSE),
       yaxis = list(showgrid = FALSE)
)
p

功能三：K线图

#从雅虎财经读取谷歌的数据
getSymbols("GOOG",src="yahoo",from="2019-01-01",to='2019-10-27')

## 'getSymbols' currently uses auto.assign=TRUE by default, but will
## use auto.assign=FALSE in 0.5-0. You will still be able to use
## 'loadSymbols' to automatically load data. getOption("getSymbols.env")
## and getOption("getSymbols.auto.assign") will still be checked for
## alternate defaults.
## 
## This message is shown once per session and may be disabled by setting 
## options("getSymbols.warning4.0"=FALSE). See ?getSymbols for details.

## [1] "GOOG"

#使用chartSeries()函数的默认形式绘制K线图
chartSeries(GOOG)

#设定参数，白色背景，蜡烛图为红色和绿色
chartSeries(GOOG,theme = 'white',
            name = '谷歌',
            up.col = 'red',
            dn.col = 'green')

#只绘制K线图，不绘制成交量
chartSeries(GOOG,theme = 'white',
            name = '谷歌',
            TA=NULL,
            up.col = 'red',
            dn.col = 'green')

#加入5日、10日均线
chartSeries(GOOG,theme = 'white',
            name = '谷歌',
            up.col = 'red',
            dn.col = 'green',
            TA =c(addMACD(),
                  addSMA(n=5,col="orange"),
                  addSMA(n=20,col="blue")))

功能四：1 DAY PERFORMANCE条形图

#绘制沪深300成分股中按行业分类的1 DAY PERFORMANCE条形图
#读取2019-11-01当天沪深300的成分股数据
hs300<- read_excel("C:/Users/thinkpad/Desktop/R/hs_300.xlsx")
# 筛选包括公司代码、名称、行业、收盘价格、业绩、市值的数据
data1<-select(hs300,code,names,sector,price,change,mc)
# 计算各行业的业绩平均值
sector_per_avg=tapply(data1$change, data1$sector,mean)
# 取绝对值
sector_per_avg_ab=abs(sector_per_avg)

# 设置一个字符向量代表行业
a<-c('A','B','C','D','E','F','G','I','J','K','L','M','N','Q','R')
# 合并行业和行业业绩均值两列
sum_sector<-cbind.data.frame(a,sector_per_avg)
sum_sector_ab<-cbind.data.frame(a,sector_per_avg_ab)

# 画出分行业1 DAY PERFORMANCE条形图
ggplot(data=sum_sector_ab, aes(x=a,y=sector_per_avg_ab,fill=sector_per_avg))+
  geom_bar(stat="identity",position="identity")+
  coord_flip()+# 把x轴和y轴互换
  geom_text(aes(label = round(sector_per_avg,2), vjust = 0.5, hjust = -0.2))+# 添加条形图标签
  scale_y_continuous(limits=c(0,6))+# 设置y轴坐标范围为0-6
  scale_fill_gradientn(colours=c("red","brown4","darkgreen","forestgreen","green3","green"))+
  # 设置条形图的颜色
  labs(x="sector",y="change(%)")+# 添加横纵坐标标题
  ggtitle('1 DAY PERFORMANCE %')# 添加图表标题

功能五：股票涨跌数量堆积条形图

# 绘制沪深300成分股中股价上涨、下跌、持平的股票数量的堆积条形图
# 读取2019-11-05数据
dat <- read_excel("C:/Users/thinkpad/Desktop/R/HS300comp.xlsx")
# 修改列名称
colnames(dat) <- 
  c("Stkcd", "Stknm", "SMA50", "Industry", "Return", "Close", "Mktvl")
# 新增两列，分别表示当日涨跌和与均线的关系
dat <- dat %>%
  mutate(BullBear = ifelse(Return > 0, "Advancing", 
                           ifelse(Return == 0, "Zero", "Declining")),
         UpDown50 = ifelse(Close >= SMA50, "Above", "Below"))

# 提取当日涨跌相关的数据
dat.home.1 <- dat %>%
  group_by(BullBear) %>%
  summarise(Stocks = n()) %>%
  mutate(Stocks_ratio = Stocks / 300,
         HS300 = 1,
         ys = c(0.1, 0.9, 0.5),
         yl = paste(round(Stocks_ratio * 100, 1), "%", sep = ""))
dat.home.1$yl[3] <- ""

# 设定当日涨跌变量的因子水平
dat.home.1$BullBear <- 
  factor(dat.home.1$BullBear, 
         levels = c("Declining", "Zero", "Advancing"),
         ordered = T)
# 显示数据
dat.home.1

## # A tibble: 3 x 6
##   BullBear  Stocks Stocks_ratio HS300    ys yl   
##   <ord>      <int>        <dbl> <dbl> <dbl> <chr>
## 1 Advancing    211       0.703      1   0.1 70.3%
## 2 Declining     75       0.25       1   0.9 25%  
## 3 Zero          14       0.0467     1   0.5 ""

# 画出当日涨跌股票数量分布的堆积条形图
ggplot(dat.home.1, aes(x = HS300, y = Stocks_ratio, fill = BullBear)) +
  geom_bar(stat = "identity", width = 0.5) + # width设置宽度
  scale_fill_manual(values = c("#de7e7e", "grey", "#83ca83")) + # 设置颜色
  annotate("text", x = 1.5, y = 0.15, # 上方文字显示
           label = dat.home.1$BullBear[1], 
           size = 6) +
  annotate("text", x = 1.5, y = 0.05, 
           label = dat.home.1$Stocks[1], 
           size = 6, 
           colour = "#00B060") +
  annotate("text", x = 1.5, y = 0.85, 
           label = dat.home.1$BullBear[2], 
           size = 6) +
  annotate("text", x = 1.5, y = 0.95, 
           label = dat.home.1$Stocks[2], 
           size = 6, 
           colour = "#FF4500") +
  geom_text(y = dat.home.1$ys, # 百分比数值显示
            label = dat.home.1$yl, 
            size = 9,
            colour = "white") +
  xlim(0, 2) +
  coord_flip() + # 坐标轴翻转
  theme(panel.background = element_blank(), # 设置主题
        axis.title =  element_blank(),
        axis.ticks = element_blank(),
        axis.text = element_blank(), 
        legend.position = "none")

功能六：股票业绩分布条形图

# 绘制沪深300成分股中业绩高于和低于50日均线水平的股票分布条形图
# 提取与50日均线相关的数据
dat.home.2 <- dat %>%
  group_by(UpDown50) %>%
  summarise(Stocks = n()) %>%
  mutate(Stocks_ratio = Stocks / 300,
         HS300 = 1,
         ys = c(0.1, 0.9),
         yl = paste(round(Stocks_ratio * 100, 1), "%", sep = ""))

dat.home.2$UpDown50 <- 
  factor(dat.home.2$UpDown50, 
         levels = c("Below", "Above"),
         ordered = T)

# 显示数据
dat.home.2

## # A tibble: 2 x 6
##   UpDown50 Stocks Stocks_ratio HS300    ys yl   
##   <ord>     <int>        <dbl> <dbl> <dbl> <chr>
## 1 Above       145        0.483     1   0.1 48.3%
## 2 Below       155        0.517     1   0.9 51.7%

# 画出超过、低于50日均线的股票分布条形图
ggplot(dat.home.2, aes(x = HS300, y = Stocks_ratio, fill = UpDown50)) +
  geom_bar(stat = "identity", width = 0.5) + 
  scale_fill_manual(values = c("#de7e7e", "#83ca83")) + # 设置颜色
  annotate("text", x = 1.5, y = 0.15, # 上方文字显示
           label = dat.home.2$UpDown50[1], 
           size = 6) +
  annotate("text", x = 1.5, y = 0.05, 
           label = dat.home.2$Stocks[1], 
           size = 6, 
           colour = "#00B060") +
  annotate("text", x = 1.5, y = 0.85, 
           label = dat.home.2$UpDown50[2], 
           size = 6) +
  annotate("text", x = 1.5, y = 0.95, 
           label = dat.home.2$Stocks[2], 
           size = 6, 
           colour = "#FF4500") +
  geom_text(y = dat.home.2$ys, 
            label = dat.home.2$yl, 
            size = 9,
            colour = "white") +
  annotate("text", x = 1.5, y = 0.5, # 百分比数字显示
           label = "SMA50", size = 10) +
  xlim(0, 2) +
  coord_flip() + 
  theme(panel.background = element_blank(), # 设置主题
        axis.title =  element_blank(),
        axis.ticks = element_blank(),
        axis.text = element_blank(), 
        legend.position = "none")

功能七：1 DAY PERFORMANCE 谱图

#绘制沪深300成分股中显示行业及公司的1 DAY PERFORMANCE
# 计算行业股票总市值
ind.mktvl <- dat %>%
  group_by(Industry) %>%
  summarise(sum.mktvl = sum(Mktvl))

# 计算绘图所需数据
dat.2 <- dat %>% 
  left_join(ind.mktvl, by = "Industry") %>%
  mutate(Mktvl_ratio = Mktvl / sum.mktvl, # 计算市值在行业内占比
         Label = ifelse(Mktvl_ratio > 0.09, Stknm, "")) %>% # 市值在业内占比达到0.09显示名称
  arrange(Industry, desc(Return)) %>%
  plyr::ddply("Industry", transform, Label_y = cumsum(Mktvl_ratio) - 0.5*Mktvl_ratio)

# 画出分行业及行业内部分公司的1 DAY PERFORMANCE SPECTRUM
ggplot(dat.2, aes(x = Industry, y = Mktvl_ratio, fill = Return)) +
  geom_bar(stat = "identity", width = 0.75) + 
  scale_fill_gradient2(low = "#00ff00", mid = "#000200", high = "#ff0000") + # 设置颜色
  geom_text(aes(y = Label_y, label = Label), size = 2.9, colour = "white") + # 显示股票名称
  scale_y_continuous(expand = c(0, 0)) +
  coord_flip() + 
  labs(title = "1 DAY PERFORMANCE SPECTRUM") + # 设置标题文本
  theme(panel.background = element_blank(),  # 设置主题
        axis.title =  element_blank(),
        axis.ticks = element_blank(),
        axis.text.x = element_blank(), 
        legend.position = "none",
        plot.title = element_text(hjust = -0.4))

Function of finviz.com

ZHR,MY

2019/11/22

一、前期准备

（一）下载并运行所需的packages

（二）导入数据

二、功能实现

功能一：板块层级图

功能二：气泡图

功能三：K线图

功能四：1 DAY PERFORMANCE条形图

功能五：股票涨跌数量堆积条形图

功能六：股票业绩分布条形图

功能七：1 DAY PERFORMANCE 谱图